Category
AI Agents
Autonomous agents, LLM applications, and intelligent systems
// 12 articles filed
// FIG. CAT-AI-A
PristrenPristrenAutonomous agents, LLM applications, and intelligent systems
// 12 articles filed
Harness engineering is OpenAI's approach to building agentic systems with Codex. This post explains the core ideas, shows concrete code, and discusses tradeoffs for production use.
Mahmudul Haque Qudrati
CEO & ML Engineer
Skills teach the agent your workflow; MCP connects live systems. Here is when to use each — and the hybrid pattern HN devs settled on in 2026.
Mahmudul Haque Qudrati
CEO & ML Engineer
How to orchestrate multiple specialized AI agents to solve complex, multi-step business problems. Explore communication protocols and handovers.
Mahmudul Haque Qudrati
CEO & ML Engineer
Agents without memory repeat themselves, forget context, and fail on multi-session tasks. Here is how short-term, long-term, and episodic memory work and how to implement each.
Mahmudul Haque Qudrati
CEO & ML Engineer
LlamaIndex is purpose-built for RAG and document Q&A. Here is how its core components work and when to choose it over LangChain.
Mahmudul Haque Qudrati
CEO & ML Engineer
Computer use agents can click, type, and navigate a real desktop. Here is what the technology can actually do, where it still fails, and when it beats a proper API integration.
Mahmudul Haque Qudrati
CEO & ML Engineer
Browser agents let LLMs control a real web browser to navigate, click, fill forms, and extract data. Here is how they work, when they are worth the cost, and when they are not.
Mahmudul Haque Qudrati
CEO & ML Engineer
Tool use is how LLMs take actions in the world. These design patterns make the difference between an agent that works reliably and one that hallucinates parameters and loops forever.
Mahmudul Haque Qudrati
CEO & ML Engineer
Deploying agents to production reveals failure modes that benchmarks never show. Here is what actually breaks and the patterns that keep agents stable under real conditions.
Mahmudul Haque Qudrati
CEO & ML Engineer
Three tools claim to be AI software engineers. Here is an honest comparison of what each actually does well, what the benchmark numbers mean, and when to reach for each one.
Mahmudul Haque Qudrati
CEO & ML Engineer
AutoGen lets you build systems where multiple AI agents collaborate, execute code, and involve humans in the loop. Here is how it works, when to use it, and the real tradeoffs you'll face in production.
Mahmudul Haque Qudrati
CEO & ML Engineer
Basic RAG retrieves the wrong chunks and loses context across chunk boundaries. Advanced techniques including hybrid search, HyDE, re-ranking, and agentic retrieval fix these problems systematically.
Mahmudul Haque Qudrati
CEO & ML Engineer
Deep dives into ML algorithms, models, and applications
AI trends, techniques, and real-world implementations
How LLMs work, honest comparisons, and production usage
Every technique that works — with real examples
Claude Code, Cursor, Copilot, open-source tools reviewed honestly
Local LLMs, open models, free AI infrastructure
Fewer tokens, cheaper APIs, local alternatives with real numbers
Benchmarks explained, evaluation frameworks, model testing
LLM SEO, AI SEO, Google AI Overviews, developer marketing
iOS, Android, and cross-platform mobile app development
Modern web technologies, frameworks, and best practices
Data analysis, visualization, and engineering insights